Date: Wed, 4 Apr 2007 15:18:11 0400
ReplyTo: "Burleson,Joseph A." <burleson@up.uchc.edu>
Sender: "SPSSX(r) Discussion" <SPSSXL@LISTSERV.UGA.EDU>
From: "Burleson,Joseph A." <burleson@up.uchc.edu>
Subject: Re: Chisquared and Chisquared test for trend comparison
InReplyTo: <7.0.1.0.2.20070404122907.037a3008@mindspring.com>
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Richard:
The last 6 large (n = 400 to 6,000) clinical trials I analyzed all had
age perfectly normally distributed (i.e., skewness between .20 and
+.20). On the other hand, I, too, have seen age not be normal (e.g.,
Poisson distributions, Ushaped distributions, etc.). One cannot assume
that it is one way or the other for no specific reason.
Sorry to be so nitpicky, but the Central Limit Theorem has nothing at
all to do with whether a population OR a single sample is normal or
nonnormal. The CLT has to do with "sampling" distributions. Repeated
sampling of a certain sample size n, of a population (continuous
variable) distribution, whether the population distribution is normal or
not, but which has a mean and an SD, will produce a set of means which
is normally distributed (Pagano & Gauvreau, 2000; Hays, 1973).
The CLT is almost always born out when the n of the sample that is
repeated being taken is >=40, and at least 50 repeated samples are
taken. I am looking for the place where these bets are made!
I accept cash, checks, VISA or future promises.
Joe Burleson
Original Message
From: Richard Ristow [mailto:wrristow@mindspring.com]
Sent: Wednesday, April 04, 2007 2:01 PM
To: Burleson,Joseph A.; SPSSXL@LISTSERV.UGA.EDU
Subject: Re: Chisquared and Chisquared test for trend comparison
Another amicus remark  I seem to be making a lot, lately 
At 10:41 AM 4/4/2007, Burleson,Joseph A. wrote:
>[...] when you have a (presumably) parametric, hopefully normally
>distributed variable such as age [...]
If my principles and the gullibility of others permitted, I would get
very rich betting against the distribution of ages being normally
distributed, in any study.
The big reason for expecting normal distributions to be common, is the
central limit theorem. Its exact hypotheses will rarely be satisfied
with real data. However, if a quantity may reasonably be modeled as the
sum of a number of independent random quantities of similar variance,
it's reasonable to take it as approximately normal.
However ages are generated, this isn't how.
